[David Gavaghan:] Mathematics is increasingly needed in biology
because what we're trying to do,
to address some of the most pressing questions in medical research in the 21st century,
is turn biology into the same sort of predictive science that physics is already.
In general, what we are trying to do...
is understand how the heart works in a predictive and quantitative way,
so that we can actually write down mathematics that describes how the heart works,
and then use that mathematics to predict how the heart is going to behave in the future.
In particular, what we'd like to look at is whether a new drug,
that's potentially being introduced by a pharmaceutical company,
is likely to cause side effects to the heart which are dangerous.
I think everyone has heard of various drugs that have been brought to market,
that eventually caused cardio-toxic side effects and even killed people.
[Denis Noble:] The heart has two major aspects to its mechanism.
Most people will think of it as a pump that moves blood through the body,
and that is its primary function: to pump the blood.
But how is that controlled?
It is controlled by electrical changes in the heart itself.
That process of the electrical waves spreading over the whole heart
is actually generated by many tiny objects that we call myocytes
-- that is muscle cells.
Each muscle cell has a membrane around it.
In that membrane there are proteins that carry charged particles (we call them 'ions')
-- sodium, potassium, chloride and other ions --
across from one side of the membrane to the other.
And that is what carries an electric current.
It's the carrying of that electric current that generates, in each cell, a wave,
and then that cell communicates with the next cell,
that communicates with the next one,
and so the wave passes over the whole heart.
And every time it passes over each cell,
that electrical wave triggers the cell itself to contract,
to produce a small movement.
When you add up all of those small movements,
you've got the whole heart beating away.
[David Gavaghan:] What we're interested in is how a drug will interact with an individual muscle cell
and change what we call the electrophysiology
-- the way that electrical excitation spreads through the heart.
And what we can do in the mathematics is mimic what a cell does.
There is a software that runs to keep airplanes up in the sky
and make sure they don't crash into one another.
That software is written to very, very high specifications.
It's called safety-critical software.
It's safety-critical because if something goes wrong, a catastrophe happens.
Medical and biological software that is modelling the way processes happen in the body...
and might be used for drug design,
ought to be developed to the same high specification.
If we're going to use it to make decisions about individual patients it's got to be right,
we've got to be absolutely confident in the software.
[Gary Mirams:] We use computational models
to put together information from different experiments that the pharmaceutical companies do.
They can screen how much a drug compound blocks particular, individual channels
and then we use the computational model to put that information together to
make a prediction for what will happen to a whole cell or a whole organ.
[David Gavaghan:] The development of a new drug, whatever it's for, is a very long and costly process.
If a drug fails at Phase 3 in clinical trials -- the very last stage,
the drug company will have spent something between $500 million and $1 billion
on getting that drug to that stage.
That money is, in effect, wasted -- that drug doesn't come to market.
That's one of the reasons that drugs cost so much.
People like GSK and AstraZeneca
-- we also work with the Food and Drug Administration in the US --
are happy to trust our code because that's the way it's been developed.
It's also completely open source so everybody can look at it.
You can come onto our website and download it yourself.
There are lots of tutorials, it's completely open, you can see everything that we do.
[Denis Noble:] In terms of taking the multiple actions of drugs seriously
and computing them,
the answer certainly is that we're at a new age
because up till now, what's tended to be the way of looking at a problem with drugs, is to say:
they've got a major action -- that's the main target -- and all the other effects are side effects.
We're saying, "wait a minute, the other effects may be very important."
It's in combination that you can understand the action of your compound